Narrating Complexity: Exploring Multi-Actor Timelines

The Narrating Complexity project focuses on developing novel visual analytics approaches for analysing and tracing complex conversations among multiple actors in a collection of timelines. These forms of conversation can be observed in environments such as social media, legislative assemblies, or collaborative code repositories. While it is easy to follow a single person conversation that contains minimal communication exchange, as the number of parties increases, so do the communication exchanges, thus making it harder to determine the source, the target, key influencers, and the full nature of interactions between the involved parties.

This project aims to present a visual analytics approaches to untangle the ‘cat’s cradle’ of complex and multi-actor timelines through thematic provenance tracing, machine-learning, and composite visualizations. The problem of visualizing such data sets has a new urgency given the growth in social media and other forms of internet-based interactions.

This is the index page for applications and demos from the Narrating Complexity project. Available pages:

Quill Voting PCA dashboard

Quill Person Visualizer